Dynamic Channel Allocation Method for UAVs Based on Stackelberg Game in Interference Environment

When unmanned aerial vehicles (UAV) operate in large-scale swarms, the simultaneous access of numerous UAVs to the task area's frequency bands leads to increasingly congested spectrum. This congestion can result in interference among multiple users within a single channel and exacerbates the problem of spectrum resource scarcity. Additionally, the open nature of wireless networks exposes UAV communications to threats such as spoofing, eavesdropping, and interference, which significantly compromise the security and reliability of information transmission. Therefore, researching dynamic spectrum allocation techniques for UAV swarms under malicious interference conditions is crucial for effectively mitigating external malicious interference and achieving efficient spectrum resource utilization. This paper proposes a dynamic resource allocation algorithm based on the Stackelberg game to effectively reduce or avoid the impact of interfering devices on UAV swarms. It constructs a dynamic spectrum allocation model based on the Stackelberg game and designs a benefit function aimed at maximizing throughput. This approach links individual optimization with global optimization, where the improvement in the benefit for a single UAV user enhances the potential function of the game, thereby increasing the overall throughput of the UAV swarm. The algorithm enables both interfering devices and UAV users to adjust their optimal channel allocation strategies based on historical experience and current environmental information, ultimately achieving a stable equilibrium and effectively enhancing the system's total throughput to maximize benefits.